Determination of iodine content in foods produced by family farmers

Abstract

Monitoring iodine consumption is important for preventing related diseases. Objective: quantify the iodine content in foods produced by family farmers in the Geographic Region of Viçosa, Minas Gerais, Brazil. Methods: samples of lettuce, cabbage, beans, cornmeal, milk, honey, eggs, coffee powder and cheese were collected from 306 households in eight cities. The colorimetric method was used to quantify iodine in food samples. Data analyzes were carried out using the Statistical Program for Social Science (SPSS) version 21.0. It was verified whether there was a difference in the concentration of iodine in foods between different cultivars, cities and seasons using the Mann Whitney and Kruskal-Wallis test, with multiple comparisons using the Dunn test. Results: 580 samples were analyzed. No difference was found between lettuce, cabbage and bean cultivars. There was a difference between cities in the iodine content of eggs (p ≤ 0.001), cheese (p = 0.028) and milk (p = 0.001). No difference was found between the seasons regarding the iodine content in cabbage and lettuce. Conclusion: the determination of iodine in foods is characterized as an initial study for the inclusion of iodine in food composition tables.

Key words:
Food analysis; Bromatological analysis; Iodine; Rural population

Resumo

O monitoramento do consumo de iodo é importante para a prevenção de doenças relacionadas. O objetivo foi quantificar o conteúdo de iodo nos alimentos produzidos por agricultores familiares da Região Geográfica de Viçosa, Minas Gerais, Brasil. Amostras de alface, couve, feijão, fubá, leite, mel, ovo, pó de café e queijo foram coletados em 306 domicílios de oito cidades. O método colorimétrico foi utilizado para quantificação de iodo nas amostras de alimentos. As análises dos dados foram feitas no programa Statistical Program for Social Science (SPSS), versão 21.0. Foi verificado se havia diferença na concentração de iodo nos alimentos entre os diferentes cultivares, cidades e estações do ano utilizando o teste Mann Whitney e Kruskal-Wallis, com comparações múltiplas pelo teste de Dunn. Foram analisadas 580 amostras. Não foi encontrada diferença entre os cultivares de alface, couve e feijão. Houve diferença entre as cidades no conteúdo de iodo para ovos (p ≤ 0,001), queijo (p = 0,028) e leite (p = 0,001). Não foi encontrada diferença entre as estações do ano quanto ao conteúdo de iodo na couve e na alface. A determinação de iodo nos alimentos caracteriza-se como um estudo inicial para a inclusão do iodo nas tabelas de composição de alimentos.

Palavras-chave:
Análise de alimentos; Análise bromatológica; Iodo; População rural

Resumen

El control de la ingesta de yodo es importante para prevenir enfermedades relacionadas. Objetivo: cuantificar el contenido de yodo en alimentos producidos por agricultores familiares de la Región Geográfica de Viçosa-Minas Gerais, Brasil. Métodos: se recolectaron muestras de lechuga, repollo, frijoles, harina de maíz, leche, miel, huevos, café en polvo y queso de 306 hogares en ocho ciudades. Se utilizó el método colorimétrico para cuantificar el yodo en muestras de alimentos. Los análisis de datos se realizaron utilizando el Programa Estadístico para Ciencias Sociales (SPSS) versión 21.0. Se verificó si existía diferencia en la concentración de yodo en los alimentos entre los diferentes cultivares, ciudades y estaciones del año mediante las pruebas de Mann Whitney y Kruskal-Wallis, con comparaciones múltiples mediante la prueba de Dunn. Resultados: se analizaron 580 muestras. No se encontraron diferencias entre los cultivares de lechuga, repollo y frijol. Hubo diferencia entre ciudades en el contenido de yodo de los huevos (p ≤ 0,001), queso (p = 0,028) y leche (p = 0,001). No se encontraron diferencias entre estaciones en cuanto al contenido de yodo en el repollo y la lechuga. Conclusión: La determinación de yodo en alimentos se caracteriza por ser un estudio inicial para la inclusión de yodo en las tablas de composición de alimentos.

Palabras clave:
Análisis de alimentos; Análisis bromatológico; Yodo; Población rural

Introdução

Iodine is an essential micronutrient for the proper functioning of the body. It participates in the formation of thyroid hormones, triiodothyronine (T3) and thyroxine (T4), which are important for the development of individuals. Inadequate intake of this micronutrient can result in the development of goiters, cretinism in children, increased infant mortality, and a range of other conditions that impair both the physical and mental development of humans. It is regarded as the leading preventable cause of brain damage in children^1,2.

To address this deficiency, various strategies have been implemented globally, prompting countries to develop public policies aimed at reducing barriers to accessing adequate food sources. This is particularly important given that not all segments of the population have regular access to oysters, mollusks, shellfish, and saltwater fish, which are among the primary dietary sources of iodine. Other sources include milk and eggs, provided that the animals receive feed containing sufficient iodine and that the soil where their feed crops are grown is adequately enriched with this nutrient³.

Low iodine levels in water and soil are common in many regions around the world, contributing to the emergence of deficiency-related conditions. A widely adopted solution to address this issue is the iodization of table salt to help ensure adequate iodine intake among the population^4-6.

Recommendations for daily iodine intake vary according to age group and physiological status. For preschool children (0-59 months), an intake of 90 μg/day is recommended; for children and adolescents (6-12 years), 120 μg/day; for adolescents over 12 years and adults, 150 μg/day; and for pregnant and lactating women, 250 μg/day⁷.

Of the 138 countries with available Urinary Iodine Concentration (UIC) data, 108 have adequate iodine status, while 20 remain deficient. Gaps in salt iodization programs and in meeting dietary needs continue to pose challenges and may negatively affect the economic development of these populations⁸. Brazilian studies using national data indicate a prevalence of iodine deficiency of 36.7% among pregnant women^9,10 and 10.11% among schoolchildren¹¹.

In Brazil, 98% of households use iodized salt. However, factors such as manufacture, storage, distribution and domestic handling of this culinary ingredient can lead to changes in the available iodine content, as found in 12.4% of samples analyzed by the National Health Surveillance Agency. In addition, there is still the use of non-iodized salt and homemade seasonings, which can impact iodine intake. Therefore, evaluating only the iodine content in salt, without considering the contribution of other foods, is insufficient to determine whether the population’s iodine needs are being met.

In contrast to iodine deficiency, excessive iodine intake can also lead to health problems, including the development of conditions such as autoimmune thyroiditis, thyroid cancer, and others. Therefore, monitoring iodine intake has become an important measure for disease prevention and health promotion¹⁶.

An effective approach for monitoring and assessing the nutritional status of micronutrients involves using instruments that measure dietary intake. Although Urinary Iodine Concentration (UIC) is a biomarker of recent iodine intake, it can be affected by factors such as renal clearance, recent consumption of iodine-rich foods, and the use of supplements, which may result in overestimation of actual intake. As a result, it does not adequately capture the long-term impact of iodine consumption on nutritional status¹⁰.

Assessing dietary intake can help address this gap; however, it depends on the availability of food composition tables and nutritional information that details the iodine content in foods. In Brazil, there is still a lack of analytical data on the iodine content of locally produced foods^17,18.

The iodine content in food can be influenced by environmental factors such as climate, soil composition, and iodine concentration in water^5,6. Consequently, relying on iodine content data from other countries or regions can lead to inaccurate estimations, either underestimating or overestimating the actual iodine levels present in local foods. In light of this, the objective of this study was to analyze the iodine content of foods produced by family farmers in the Geographical Region of Viçosa, Minas Gerais, Brazil.

Methods

Study design and population

The sample size for the population to be visited for food collection was calculated using the OpenEpi® program, following equation 1:

$\text{n}=\frac{EDF{F}^{\star }\text{N}p(1-p)}{\left(\frac{d2}{Z21}-\frac{\alpha }{2(\text{N}-1)+\text{p}(1-9)}\right)}$ 1

The total rural population was considered for the population size (n) with n = 31,090 ¹⁹. The prevalence (p) of iodine deficiency was set at 14.1% based on data for rural schoolchildren, since no national data for adults are available²⁰. A tolerable error (d) of 5% was adopted, with a 95% confidence level, a standard normal distribution (Z) score of 1.96, and a design effect (EDFF) of 1.5 for random samples from rural areas²¹. This resulted in a required sample size of 278 individuals.

To account for potential dropouts, incomplete data, and control of confounding factors²¹, an additional 10% was added, resulting in a final sample of 306 farmers. These farmers were randomly selected and visited for sample collection in the rural area of the Immediate Geographic Region of Viçosa, Minas Gerais, Brazil (Table 1).

Table 1
Distribution of the number of rural properties visited by municipality in the immediate geographic region of Viçosa, Brazil, 2022.

City	Population			Proportion of residents living in rural areas (%)*	Number of properties visited
	Total	Urban	Rural
Cajuri	4,047	2,096	1,951	6	19
Canaã	4,628	1,859	2,769	9	27
Coimbra	7,054	5,156	1,898	6	19
Ervália	17,946	9,470	8,476	27	83
Paulo Cândido	9,271	4,936	4,335	14	43
São Miguel do Anta	6,760	3,746	3,014	10	30
Teixeiras	11,355	7,623	3,732	12	37
Viçosa	72,220	67,305	4,915	16	48

• *The proportion was calculated based on the number of residents in rural areas in each municipality.
• Source: Authors.

Characterization of the region

The Immediate Region of Juiz de Fora, Minas Gerais, Brazil, consists of 146 municipalities, which are organized into 10 Immediate Geographic Regions, including Viçosa. The Viçosa region encompasses 12 municipalities located in the Mata Zone of Minas Gerais. The climate is tropical and humid tropical, with an average temperature of 18 °C.

Characterization of the food sample

Food collection was carried out through home visits to 306 properties belonging to the selected family farmers, distributed across the eight participating municipalities. The selection of foods to be analyzed was based on prior studies conducted in the same region and on the availability of food produced on the farms^22,23. The selected foods included lettuce, kale, beans, cornmeal, milk, honey, eggs, coffee powder, and cheese. In each household, a sample of these foods was requested; however, not all households had all items available for collection.

The collected samples were stored in thermal containers and transported at ambient temperature to the Laboratory of Food Analysis and Chemistry of the Department of Food Technology at the Federal University of Viçosa, where they were cataloged. All samples were frozen and stored at -20° C, except for the egg samples, which were refrigerated at 4° C for up to two days.

The collection date was recorded to allow for comparison of seasonal variation and its possible impact on iodine concentration in cabbage and lettuce samples. These foods were chosen due to their short growing cycles and the fact that they were harvested directly from the farmers’ gardens. Sampling and analysis took place between July 2021 and August 2022.

Disclosure of ethical standards

This study is part of the project entitled “Factors associated with iodine deficiency in family farmers in the Mata Zone of Minas Gerais,” which was approved by the Ethics Committee for Research Involving Human Subjects at the Federal University of Viçosa, under opinion number 2.496.986. Participants gave their informed consent after reading the Free and Informed Consent Form.

Determination of iodine in food

The colorimetric method developed by Moxon et al.²⁴, which is widely recognized and validated for iodine analysis in food samples, was used with adaptations by Perring et al.²⁵. This technique relies on the colorimetric determination of iodine, based on its catalytic role in the destruction of a ferric thiocyanate complex by the nitrite ion, catalyzed by iodide, which leads to a decrease in the reddish color. Absorbance was measured at 454 nm using a spectrophotometer. The iodine content of food samples was quantified by comparing measurements to a calibration curve prepared each day of analysis.

Pre-preparation of food samples

Lettuce and kale were mixed, frozen, and grated with a household grater until a paste was formed, then stored in 50 mL polyethylene containers. Samples of 0.500 g were analyzed in duplicate, and the remaining material was frozen at -20° C.

Beans and corn were ground using an Analytical A11 Basic Mill knife mill, sieved through a stainless-steel sieve with a 0.053 mm opening, and stored in 15 mL Falcon tubes at -20° C until analysis.

Cheese samples were macerated using a mortar and porcelain pestle until a paste was formed and were analyzed immediately. A 0.500 g portion was taken in duplicate, and the remainder was frozen at -20° C.

Eggs were refrigerated, then separated from their shells and mixed thoroughly with the yolk and egg white in a polyethylene container. Manual stirring for one minute was performed to produce a homogeneous mixture, which was then immediately analyzed for iodine content.

Samples of cornmeal, milk, honey, and coffee powder were mixed with a glass rod inside the collection container prior to weighing iodine quantification. Portions of 0.500 g were analyzed in duplicate, and any remaining sample was frozen at -20° C.

Sample preparation for iodine determination

Approximately 0.500 g of each pre-prepared food sample was weighed on an analytical balance into clean, dry, labeled crucibles that had been previously demineralized. Using a 1000 μL single-channel pipette, 1.0 mL of 10% zinc sulfate solution and 1.0 mL of 30% (m/v) potassium carbonate solution were added to each crucible. The mixture was then homogenized with a glass rod to form a paste, and any residue adhering to the rod was washed off with a small amount of ultrapure water and returned to the crucible. The crucibles were then placed in a controlled oven at 95° C for approximately 14 hours.

After drying, the crucibles were covered and transferred to a muffle furnace, initially at 100° C, with the temperature gradually increased to 550° C, where they remained for 60 minutes. After ashing, the crucibles were removed using tongs and allowed to cool, then 1.0 mL of the 10% zinc sulfate solution was added to the resulting dark ash. The paste was mixed with a glass rod, and any residue adhering to the rod was rinsed back into the crucible with ultrapure water. The drying procedure was repeated in an oven at 95 °C for 14 hours, followed by ashing in the muffle furnace at 550° C for 60 minutes until light or white ash was obtained.

Once cooled, the ash was transferred to a 50 mL volumetric flask using a glass rod and ultrapure water, and the final volume was made up to the mark. The solution was then transferred to 15 mL Falcon tubes and centrifuged at 957 for 5 minutes using an Excelsa II Centrifuge (FANEM brand). The resulting supernatant was used for iodine quantification.

Analytical curve of iodine

A potassium iodide (KI) standard solution was prepared by weighing 0.5232 g of KI with an analytical balance, using a 5 mL beaker and a spatula. The KI was dissolved in ultrapure water, transferred to a 100 mL volumetric flask, filled to volume with ultrapure water, and homogenized, yielding a standard iodine solution of 4 g L-1.

From this stock solution (4 g L-1), 10 mL were removed with a 10 mL volumetric pipette and transferred to a 1000 mL volumetric flask, which was filled with ultrapure water and homogenized, producing a 40 mg L-1 iodine standard solution. Next, 50 mL of the 40 mg L-1 solution was transferred using a 50 mL volumetric pipette to a 1000 mL volumetric flask, topped up with ultrapure water, and homogenized to obtain a 2000 μg L-1 iodine standard solution.

Aliquots of 0.0, 2.0, 4.0, 6.0, 8.0, 10.0, and 12.0 mL of this 2,000 μg L-1 solution were pipetted into separate 100 mL volumetric flasks. Each flask received 1 mL of the 30% (m/v) potassium carbonate solution, and the volume was completed with ultrapure water. The contents were transferred to amber vials, producing final iodine concentrations of 0.0, 40.0, 80.0, 120.0, 160.0, 200.0, and 240.0 μg L-1 to serve as the standard iodine solutions.

In a series of 15 mL Falcon tubes, 0.5 mL of each standard solution was pipetted with a 10,000 μL single-channel micropipette, and 4.5 mL of ultrapure water was added. Next, 1.0 mL of potassium thiocyanate solution (0.023% m/v), 2.0 mL of ferric ammonium sulfate solution (7.7% m/v in 2.0 mol L-1 HNO3), and 2.0 mL of sodium nitrite solution (0.02% m/v) were added in sequence. This produced a total volume of 10 mL, resulting in final iodine concentrations of 0, 2, 4, 6, 8, 10, and 12 μg L-1, respectively. The tubes were vortexed and incubated in a thermostatic bath at 60° C for 60 minutes, then cooled in an ice bath for ten minutes.

Absorbance readings were taken at 454 nm using a Rayleigh spectrophotometer at room temperature, previously calibrated with ultrapure water. An analytical curve of absorbance at 454 nm versus iodine concentration (μg L-1) was constructed, and a linear regression equation was generated for iodine quantification. The standard iodine solutions ranged from 0 to 12.0 μg L-1, and the analytical curve was prepared in duplicate.

All reagents were supplied by Sigma Aldrich with high analytical purity. Solutions and reagents were prepared using ultrapure water produced by a Milli-Q 185 system, Type 1 ultrapure water, with a PURELAB Classic unit providing resistivity of 18.2 MΩ/cm at 25° C.

Iodine determination in food

In 15 mL Falcon tubes, 1.0 mL of the supernatant from sample centrifugation was pipetted and mixed with 4.0 mL of ultrapure water. The same sequence of reagent additions was applied as described above, and absorbance was measured at 454 nm at room temperature using a spectrophotometer calibrated with ultrapure water. All analyses were performed in duplicate, and the mean iodine concentration was expressed in μg L-1.

Statistical analysis

Data were analyzed using the Statistical Program for Social Science (SPSS), version 21.0. Descriptive statistics were calculated, reporting median, minimum, and maximum values to describe iodine concentrations in foods. The Kolmogorov-Smirnov test was used to assess normality. Non-parametric tests were applied.

Differences in iodine concentrations among cultivars, municipalities, and collection seasons were tested using the Mann-Whitney or Kruskal-Wallis tests, with multiple comparisons conducted by Dunn’s Test. A p-value of less than 0.05 was considered statistically significant.

Results

A total of 306 family farmers were visited, resulting in the collection of 580 food samples for analysis, as detailed in Table 2.

Table 2
Number of samples analyzed by cultivar or food classification produced by family farmers in the immediate geographic region of Viçosa, Brazil, 2022.

Food Item	Total number of samples analyzed
Crisphead lettuce (Lactuca sativa var. crispa) Smooth lettuce (Lactuca sativa)	31 12
Curly kale (Brassica oleracea var. sabellica) Collard greens (Brassica oleracea)	09 54
Black beans (Phaseolus vulgaris)Carioca beans (Phaseolus vulgaris)Red beans (Phaseolus vulgaris) Other beans	12 50 66 09
Cornmeal (Zea mays)	36
Milk	60
Honey	12
Egg	174
Coffee powder (Coffea arabica)	44
Cheese (“minas frescal”)*	11

• * Minas frescal cheese is classified as a semi-fat, very high-moisture cheese, intended for fresh consumption, according to the Technical Regulation of Identity and Quality of Cheeses²⁶.
• Source: Authors.

No significant differences in iodine content were found between the different cultivars of beans (p = 0.089), cabbage (p = 0.220), and lettuce (p = 0.245) (Table 3).

Table 3
Median, minimum, maximum, mean, and standard deviation of iodine concentration (µg per 100 grams) in raw foods produced by family farmers in the immediate geographic region of Viçosa, Brazil, 2022.

Food item	Median iodine (Minimum - Maximum) (µg/100g)	Mean iodine ± SD (µg/100g)
Lettuce (Lactuca sativa)	23,20 (14,82-52,12)*	26,26 ± 14,86
Kale (Brassica oleracea)	23,13 (14,39-54,93)*	26,12 ± 14,80
Beans (Phaseolus vulgaris)	22,00 (2,38-71,00)**	25,23 ± 15,91
Cornmeal (Zea mays)	21,29 (2,61- 74,52)	24,92 ± 15,50
Milk	21,22 (4,08-62,86)	23,40 ± 14,29
Honey	21,25 (0,00-49,17)	23,54 ± 14,25
Egg	20,68 (0,16-77,16)	22,83 ± 14,01
Coffee powder (Coffea arabica)	22,46 (1,00-82,11)	25,80 ± 14,83
Cheese (“Minas frescal”)	22,15 (13,62-59,91)	23,63 ± 10,13

• * No significant difference between cultivars according to the Mann-Whitney test (p > 0.05). ** No significant difference between cultivars according to the Kruskal-Wallis test (p > 0.05).
• Source: Authors.

When comparing the median iodine concentration (μg) per 100 grams of food produced by family farmers, no significant differences were observed between municipalities for lettuce (p = 0.249), cabbage (p = 0.176), beans (p = 0.089), cornmeal (fubá) (p = 0.090), honey (p = 0.076), and coffee powder (p = 0.106) (Table 4).

Table 4
Comparison of median iodine concentrations (µg per 100 grams) in raw foods produced by family farmers, by municipality of origin in the immediate geographic region of Viçosa, Brazil, 2022.

Municipality	Food item
	Median iodine concentration (minimum - maximum) (µg/100g)
	Lettuce (Lactuca sativa)	Couve (Brassica oleracea)	Bean (Phaseolus vulgaris)	Cornmeal (Zea mays)
Cajuri	34,01a (30,42-37,60)	29,89a (20,53-44,39)	27,91a (15,73-50,84)	17,86 a -
Canaã	22,46a (16,26-32,41)	32,56a (30,33-42,73)	26,73 a (6,74-67,38)	50,39 a (14,14-55,99)
Coimbra	24,14a (19,77-40,74)	19,74a (14,39-33,28)	30,95 a (11,00-64,98)	12,14 a -
Ervália	21,60a (14,82-44,47)	21,23a (17,08-38,61)	28,95 a (9,17 -71,00)	15,91 a (2,65-74,52)
Paula Cândido	34,71a (20,12-39,03)	35,56a (19,78-37,56)	20,32 a (2,38-33,39)	17,02 a (11,23-24,26)
São Miguel do Anta	28,06a -	25,22a -	22,04 a (3,57-37,01)	17,32 a (11.50-27.11)
Teixeiras	38,89a (30,94-52,12)	40,00a (19,25-54,93)	6,17 a (5,06-29,50)	8,32 a (5.25-11.38)
Viçosa	26,00a (15,77-44,26)	33,63a (23,19-45,02)	17,16 a (4,80-40,49)	12,64 a (2,61-39,96)

Municipality	Food item
	Median iodine concentration (minimum - maximum) (µg/100g)
	Milk	Honey	Egg	Coffe powder (Coffea arabica)	Cheese
Cajuri	56,89a (48,43-62,86)	-	18,91a (6,49-77,16)	48,99 a (25,32-77,24)	-
Canaã	25,67ab (20,78-35,25)	-	30,33bde (11,07-46,91)	24,03 a (12,26-76,76)	29,36a (25,39-33,34)
Coimbra	54,10a (31,57-56,99)	-	29,03cde (4,37-49,55)	27,13 a (24,83-29,44)	-
Ervália	9,49ac (4,08-22,97)	4,49 a (0,00-10,20)	18,94a (2,22-59,74)	33,97 a (17,88-82,11)	17,21bc (13,62-22,46)
Paula Cândido	22,62a (21,93-27,00)	32,60 a -	22,99a (11,30-46.85)	37,78 a (34,66-51,14)	-
São Miguel do Anta	13,03a (6,80-32,91)	7,74 a -	10,68dbcf (7,85-12,65)	20,98 a (17,11-24,85)	-
Teixeiras	17,88ad (8,67-22,44)	7,94 a -	13,06ebcf (6,77-24,02)	33,55 a (26,78-40,33)	19,21a -
Viçosa	20,25a (12,67-34,66)	45,32 a (37,84-49,17)	23,68fde (0,16-36,99)	19,58 a (1,00-72,11)	35,16bc (32,42-59,91)

• - = indicates no available data for median calculation or that food was not sampled in that municipality. Medians followed by the same letter do not differ significantly (p > 0.05) according to the Kruskal-Wallis test; medians followed by different letters differ significantly (p ≤ 0.05).
• Source: Authors.

However, significant differences in iodine concentrations in eggs were found between the municipalities of São Miguel do Anta and Viçosa (p = 0.037), São Miguel and Coimbra (p = 0.036), São Miguel and Canaã (p = 0.001), Teixeiras and Viçosa (p = 0.023), Teixeiras and Coimbra (p = 0.036), and Teixeiras and Canaã (p = 0.001). For cheese samples, a significant difference was found between Viçosa and Ervália (p = 0.031). In addition, differences in iodine content in milk were observed between Cajuri and Ervália (p = 0.009), Cajuri and Teixeiras (p = 0.033), and Cajuri and Canaã (p = 0.009) (Table 4).

No significant seasonal differences were found in the iodine content of cabbage (p = 0.265) and lettuce (p = 0.224).

Discussion

In this study, we aimed to analyze the iodine content in foods produced by family farmers and found no significant differences in iodine levels in plant-based foods and honey across different cultivars, seasons, or municipalities. However, for animal-based foods, differences were observed between municipalities.

Iodine levels in food can vary due to deficiencies or excesses present in animals and plants^5,6,27. Variations in this micronutrient can be attributed to geographic factors such as soil iodine content, water, climate, environment, and food preparation methods. Understanding how these factors influence iodine availability is an important aspect of public health. For example, water iodine levels can fluctuate depending on soil characteristics, proximity to the ocean, and agricultural runoff. Another factor that may influence the iodine content in food is the use of iodine-containing fertilizers^17,28.

Iodine is an essential nutrient that must be obtained through dietary sources, and its natural availability in food directly affects nutritional status. Therefore, developing monitoring and evaluation strategies is vital to support health promotion and prevent iodine deficiency, which continues to affect populations worldwide, especially pregnant women, nursing mothers, and infants^9,10.

In this regard, the Multicenter Study of Iodine Deficiency (EMDI-Brasil) was designed to assess the nutritional profile of iodine, sodium, and potassium in mothers and children through a cross-sectional approach during pregnancy and breastfeeding. This multicenter study highlighted important gaps that need to be addressed, especially regarding iodine content in foods, since research on food intake emphasizes the need for data on the iodine content of Brazilian foods⁹.

Additionally, Silva et al. 2023¹⁰ found that beyond iodized salt, other foods such as rice, beans, eggs, milk, and bread also contribute significantly to iodine intake. These findings support the importance and relevance of this study, as it evaluated the iodine concentration in foods frequently available in households, produced by family farmers.

For plant-based foods, no significant differences were found between municipalities in this study. The absence of variation in iodine content in plant foods and honey suggests that it is appropriate to use median values for each item: Lettuce (27.03 μg/100g), Cabbage (31.23 μg/100g), Beans (24.39 μg/100g), Cornmeal (16.47 μg/100g), Honey (7.94 μg/100g), and Coffee Powder (30.34 μg/100g).

The lack of difference among municipalities for plant foods may be explained by the geographic proximity of the cities, which provides similar environmental conditions for plant growth. No significant differences were found between cultivars of lettuce, cabbage, and beans, which aligns with the limited variation reported in nutrient content across cultivars in the literature, with the exception of iron levels in beans^29,30.

For animal-based foods, including milk, cheese, and eggs (excluding honey), differences in iodine content between cities were observed. The iodine concentration in these foods can vary depending on the animals’ diets and how the products are handled. According to Ershow et al.¹⁷, livestock are frequently given food supplements to support animal health, reproduction, and weight gain in dairy and beef cattle, sheep, goats, and poultry. Additionally, substances containing iodine, such as iodophores used to clean cow udders, can transfer to milk if not properly rinsed.

Iodine levels in animal foods can also be influenced by the use of iodized salt in their preparation. For example, fresh cheess, a common food in the study region, is traditionally made from raw milk, rennet (containing chymosin and pepsin), and salt. The amount of salt used, and its iodine content, can affect the final iodine level of the cheese.

On average, iodine intake in Brazil is approximately 163.1 μg per day, as observed in studies of specific groups, such as pregnant women¹⁰. This value falls within the WHO’s recommended daily intake of 150 μg for adults but remains below the 250 μg recommendation for pregnant and breastfeeding women ⁷, indicating a gap that must be addressed through nutrition strategies such as supplementation.

According to EMDI-Brasil data, salt consumption accounts for about 45% of iodine intake¹⁰. Brazilian regulations require salt to contain 15 to 45 mg of iodine per kilogram¹⁴. However, the Household Budget Survey (POF 2017/2018) indicates that the average daily salt consumption in Brazil is 9.34 grams per person, which exceeds the recommended maximum of 5.0 grams¹³.

Despite this, culinary salt alone does not meet the total iodine requirement. The remaining 55% comes from other foods, including rice, beans, milk, and eggs. Thus, to compare the results obtained from the food analyses with national consumption data, the Figure 1 is presented.

Figure 1
Quantitative iodine consumption in the Brazilian diet, considering the median iodine content in the foods analyzed.

Among the foods analyzed in this study that have known consumption data for the Brazilian population, the total median iodine concentration was 44.95 μg/day/person. Given the recommended intake for adults of 150 μg/day, these foods contribute about 30% of the requirement. It should be noted that the foods analyzed were raw and did not undergo cooking or infusion processes, which can affect iodine content.

It is important to consider factors such as nutrient retention when estimating iodine levels in prepared foods, taking into account the nutrient content of the raw food and how much is retained after preparation. This information is essential to understand the actual nutrient levels in foods^32,33.

Regarding “coffee powder,” national consumption data refer to the brewed beverage rather than the raw ingredient. Therefore, the standard recipe in the project’s database was used, and the consumption value of 163.2 g/day/person reported in the POF 2017/2018 survey was applied¹³.

Beans showed the highest iodine content among the foods analyzed and are a staple in the Brazilian diet. However, bean consumption has declined over time, with a prevalence of 58.6% in Brazilian capitals and the Federal District in 2023³⁴. A reduction in bean consumption may contribute not only to lower iodine intake but also to deficiencies of other micronutrients, highlighting the importance of encouraging its consumption through nutrition education to promote healthy eating.

When comparing these findings with the study by Milagres et al.¹⁸, which compiled iodine content data from different food composition tables worldwide, it was found that the medians in this study were higher. However, when minimum and maximum values are considered, this study’s medians fall within those ranges, likely due to geographic variations in iodine levels similar to those found in the Immediate Geographic Region of Viçosa.

The iodine content results in this study are also consistent with the USDA food composition table (2022), although the analytical methods differ, as the USDA uses inductively coupled plasma mass spectrometry. Similarities between regions with comparable iodine levels underscore the importance of considering shared factors such as water iodine content, food production practices, and soil biogeochemistry^35,36.

A topic of growing relevance is food biofortification strategies, including soil management practices that enhance iodine levels in crops, which could increase dietary iodine intake³⁷. However, such practices require further research into the epidemiological aspects of micronutrient deficiencies, as both iodine deficiency and excess can occur within the same population²⁰.

One limitation of this study is that it analyzed raw rather than cooked foods. However, this approach was chosen due to the lack of comparable studies in Brazilian literature. Future studies should address differences in iodine content between raw and cooked foods, regional variations in iodine levels, and a broader range of foods, to provide information that supports better analysis of iodine intake in the Brazilian population³⁸.

This is the first study to analyze the iodine concentration in foods produced by family farmers using a representative sample from the Immediate Geographic Region of Viçosa, Minas Gerais, Brazil. The findings will support future research and help guide actions that promote the consumption of iodine-rich foods.

Conclusion

Determining the iodine content of foods is an important public health measure. By analyzing the foods most commonly produced and consumed by a specific group or population, it becomes possible to develop food composition tables and reliable nutritional information. This, in turn, ensures an accurate assessment of iodine intake and enables a better understanding of overall dietary quality. Such information helps identify foods that contribute to daily iodine intake and supports the development of appropriate dietary guidelines and recommendations. Moreover, these data are essential for shaping public policies and for monitoring iodine nutritional status and deficiencies.

Therefore, this study focused on analyzing the iodine content of foods produced by family farmers, addressing the significant gap caused by the lack of data on the iodine content of Brazilian foods.

Acknowledgements

We thank all participants in this study.

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• Funding
  This work was supported by the Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG - BPD 01017-22), the Coordination for the Improvement of Higher Education Personnel (CAPES), the National Council for Scientific and Technological Development (CNPq) (Call MCTIC/CNPq 2018 - Process: 439075/2018-1), and the Graduate Program in Nutrition Science and the Graduate Program in Agroecology, both at the Federal University of Viçosa (Brazil).
• Data availability statement
  The data sources adopted in the research are indicated in the article’s body.

• Chief editors:
  Maria Cecília de Souza Minayo, Romeu Gomes, Antônio Augusto Moura da Silva, Vania de Matos Fonseca

Data availability

The data sources adopted in the research are indicated in the article’s body.

Publication Dates

• Publication in this collection
  03 Aug 2026
• Date of issue
  July 2026

History

• Received
  07 July 2024
• Accepted
  07 Apr 2025
• Published
  09 Apr 2025